Computational Statistics: Predicting the Future from Sample Data

How can we uncover hidden patterns in noisy, complex data?
How can we make reliable predictions in an unpredictable world?
And how can the combination of statistical theory, data from diverse sources, and increased computing power help us predict the future?
In this age of data, and especially big data, computational statistics has become central to scientific discovery and decision-making. Therefore, this book explores the growing role of computational methods in statistical analysis, highlighting how we can transform sample data into meaningful predictions across various disciplines and domains. This volume brings together five chapters, each of which addresses a unique aspect of modern computational statistics and is ideal for statisticians, data scientists, university professors, graduate students, and researchers who seek to deepen their knowledge of computational statistics and its impact on the real world.